Bysmxms {longit} | R Documentation |
Bayesian mixed effect model with random intercepts and slopes with longitudinally measured missing data. Fits using MCMC on longitudinal data set
Bysmxms(m, n, time, group, chains, n.adapt, data)
m |
Starting number of column from where repeated observations begin |
n |
Ending number of columns till where the repeated observations ends |
time |
Timepoint information on which repeadted observations were taken |
group |
A categorical variable either 0 or 1. i.e. Gender - 1 male and 0 female |
chains |
Number of MCMC chains to be performed |
n.adapt |
Number of iterations to run in the JAGS adaptive phase. |
data |
High dimensional longitudinal data |
Gives posterior means, standard deviation.
Atanu Bhattacharjee, Akash Pawar and Bhrigu Kumar Rajbongshi
Bhattacharjee, A. (2020). Bayesian Approaches in Oncology Using R and OpenBUGS. CRC Press.
Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian data analysis. CRC press.
Fitzmaurice, G. M., Laird, N. M., & Ware, J. H. (2012). Applied longitudinal analysis (Vol. 998). John Wiley & Sons.
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data(mesrep)
Bysmxms(m=4,n=7,time="Age",group="Gender",chains=4,n.adapt=100,data=msrep)
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